---
license: other
tags:
- science
- mathematics
- reasoning
- multiple-choice
- question-answering
task_categories:
- multiple-choice
- math
- question-answering
language:
- en
size_categories:
- 1K<n<10K
---

# StreetMath Dataset

## Dataset Summary

The **Street Math dataset** is a synthetic reasoning benchmark that evaluates a model’s ability to **approximate sums of decimal prices** in everyday shopping scenarios.  
Each example presents a list of item prices, and the model must select the approximate total cost (before tax) from multiple-choice options.  

The dataset is designed to test **numerical reasoning, estimation, and handling of decimal numbers**.  
Language: **English**.  
Domain: **mathematics applied to real-world shopping tasks**. 

## Languages

- **English (en)**: prompts and options are written in plain English, with U.S. dollar formatting for prices.

## Data Instances

Example instance:

```json
{
  "id": "basket_sum_000243",
  "topic": "basket_sum",
  "subtopic": "decimal_prices",
  "prompt": "You’re buying these items: $3.55, $15.42, $4.56, $12.63, $6.08. About how much will you pay (before tax)?",
  "labels": ["A", "B", "C", "D"],
  "correct_label": "A",
  "choices": ["$43.00", "$14.11", "$42.24", "$182.80"],
  "correct_option": 0,
  "metadata": {
    "exact_value": 42.24,
    "good_value": 43.0,
    "mild_value": 14.11,
    "way_value": 182.8,
    "prices": [3.55, 15.42, 4.56, 12.63, 6.08]
  },
  "split": "test"
}
```

## Intended Uses

The Basket Sum dataset is intended for:  
- **Benchmarking language models** on basic numerical reasoning and arithmetic in natural language contexts.  
- **Evaluating estimation skills**: testing whether models can provide approximate answers rather than exact calculations.  
- **Educational and research purposes**: studying how models handle everyday math tasks such as adding decimal prices.  

This dataset is **not** intended for:  
- Financial or accounting applications.  
- Real-world shopping or economic forecasting.  
- Any critical decision-making where incorrect numerical outputs could cause harm.

## Format

- **File type:** JSON Lines (`.jsonl`)
- **Each line:** one example as a JSON object
- **Compatible with:** Hugging Face `datasets` library (`load_dataset("json", data_files="...")`)


## How to Get the Dataset

You can easily load this dataset from the Hugging Face Hub using the `datasets` library:

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("Chiung-Yi/StreetMath")

# Access the test split
test_dataset = dataset["test"]

# Example: print the first item
print(test_dataset[0])
```


## Limitations and Ethical Considerations

**Licensing**: The license is currently unspecified. For any public or commercial use, it is necessary to verify the terms with the author.


## Dataset Curators

- Original dataset created by [Chiung-Yi](https://huggingface.co/Chiung-Yi)

### Disclaimer
This dataset card was written by a community contributor to improve documentation. 
If you are the original author or know additional details, feel free to submit a pull request or open an issue to update this card.